Flaw analysis of images

ABSTRACT

Systems and methods are disclosed to provide flaw accentuation to an image in an e-commerce online marketplace. In some embodiments, a method may include receiving at an online marketplace, from a seller through the Internet, an image of an item being listed for sale at the online marketplace and text related to the item being listed for sale; determining that the item includes a flaw based on the text related to the item being listed for sale or the image of the item; creating a flaw accentuation to the image; and creating a listing in the online marketplace for the item that includes the image and the flaw accentuation to the image.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/986,486, filed on Dec. 31, 2015; the disclosure of which isincorporated herein by reference in its entirety.

TECHNICAL FIELD

This disclosure relates generally to flaw analysis of images.

BACKGROUND

E-commerce has become ubiquitous. In addition to brick and mortarestablishments, consumers can purchase goods and services frome-commerce retailers from their computer and/or mobile device.E-commerce has its drawbacks. In some cases consumers are unable to dealdirectly with a salesperson, which may lower the level of trust in apotential transaction or purchase. The distance between buyers andsellers and the anonymity of sellers may limit a buyer's ability toresolve issues with a product or service after purchase, which may alsolower trust in the engagement.

Many of these issues may be exacerbated when the seller is notassociated with the online marketplace where the goods or services arelisted for sale. For instance, in some online marketplaces sellers areable to list items for sale (or auction) through the online marketplaceand may be charged a fee by the online marketplace for this service.Once the buyer purchases the goods or services, the seller may deliverthe goods or services. This arm's length relationship between the buyerand the seller can lead a buyer to be more distrustful of a seller in anonline marketplace and/or in e-commerce. Providing e-commerce toolsand/or resources that show the trustworthiness of the seller canincrease the likelihood that a transaction may be completed.

BRIEF DESCRIPTION OF THE FIGURES

These and other features, aspects, and advantages of the presentdisclosure are better understood when the following Detailed Descriptionis read with reference to the accompanying drawings.

FIG. 1 illustrates an example architecture in which a user may interactwith the e-commerce website according to some embodiments.

FIG. 2 illustrates a block diagram of some components of the electronicmarketplace according to some embodiments.

FIG. 3 is a flowchart of an example process for listing an item in anonline marketplace according to some embodiments.

FIG. 4 is a flowchart of an example process providing flaw analysis,flaw presentation, and ranking based on the flaw analysis according tosome embodiments.

FIGS. 5A, 5B, 5C, and 5D illustrate examples of a user interface forflaw marking and/or flaw presentation according to some embodiments.

FIG. 6 is a flowchart of a process for performing flaw analysis for anitem that includes a digital display according to some embodiments.

DETAILED DESCRIPTION

Systems and methods are disclosed to determine whether an item beinglisted for sale in an online marketplace is flawed. In some embodiments,a method may receive at the online marketplace an image of an item beinglisted for sale at the online marketplace; provide a user interface tothe seller that allows the seller to indicate whether the item has oneor more flaws; provide the user with one or more digital flawaccentuation tools through the first user interface; receive through theuser interface a flaw accentuation to the image that is based on aninteraction between the user and a flaw accentuation tool; and create alisting in the online marketplace for the item that includes the imageand an application of the flaw accentuation to the image

These illustrative embodiments are mentioned not to limit or define thedisclosure, but to provide examples to aid understanding thereof.Additional embodiments are discussed in the Detailed Description, andfurther description is provided there. Advantages offered by one or moreof the various embodiments may be further understood by examining thisspecification or by practicing one or more embodiments presented.

Systems and methods are disclosed to perform flaw analysis on imagesprovided as part of an item listing in an online marketplace. In someembodiments, a presentation may be made to a potential buyer thatincludes accentuations or identification of a flaw within one or moreimages provided by the seller. In some embodiments, a flaw analysis maybe performed that may include both an implicit flaw analysis and anexplicit flaw analysis. In some embodiments, the results of the flawanalysis may be used as part of a ranking system for the item listingand/or may be used to penalize sellers that do not report flaws in theiritems.

Some embodiments may be used to increase buyer satisfaction and/orincrease the appearance of seller trustworthiness by providingopportunities for a seller to disclose and/or present flaws in an itemlisted for sale. In addition, some embodiments may be useful to anonline marketplace to motivate sellers to identify and/or present flawsto potential sellers to potentially increase both trustworthiness andincrease conversion. Such embodiments may help e-commerce and/or onlinemarketplaces overcome many challenges.

A flaw may include, for example, a scratch, chip, dent, fold, crack,water damage, stain, chip, bend, discoloration, fading, hole, ink stain,gouge, etc. A flaw may be any damage to an item that makes the item lessthan new or puts the item in a condition that a user would recognize asnot being new.

In online marketplaces where sellers may sell used items, the integrityof the online marketplace may depend at least in part on the level oftrust a buyer may have with a seller. The more open the seller is aboutthe item listed for sale, for example, the more trust the buyer may havewith the seller, which may translate into a buyer being more likely topurchase an item from the seller. Sellers that provide an open andhonest description of the flaws of an item being listed for sale aremore likely to be trusted than those that don't. A flaw analysis and/orpresentation as discussed in this document may provide an avenue toincrease the trust between buyers and sellers, which may result in ahigher rate of sales between buyer and sellers.

FIG. 1 illustrates an example architecture 100 in which a user (eitheror both a seller or a buyer) may interact with an e-commerce website.The user may access an e-commerce website, for example, using a userdevice that may include a mobile device 105 or a computer 110. The userdevice, for example, may include a smart phone, a tablet, a laptopcomputer, a desktop computer, a smart watch, or some combinationthereof. The user device may be coupled or connected to the network 115either through a wired or wireless connection.

The e-commerce web site may be hosted or maintained by a server 120,which may include one or more servers distributed locally or broadly. Insome embodiments, the server 120 may be a cloud based server system thatmay include a plurality of servers located at various locations andconnected through a network. A website hosted by the server 120 mayprovide one or more representations of items as an item listing that maybe purchased by a user. Images of these items as well as text describingthese items may be sent to a user device through the network 115 inorder to provide the item listing in the website. Users may view theimages and text using a web browser, an application, or an app on userdevices. The website may provide a marketplace whereby users may shopfor and purchase items listed as item listings in the marketplace.

The network 115 may be any network or configuration of networksconfigured to send and receive communications between devices. In someembodiments, the network 115 may include a conventional type network, awired or wireless network, and may have numerous differentconfigurations. Furthermore, the network 115 may include a local areanetwork (LAN), a wide area network (WAN) (e.g., the Internet), or otherinterconnected data paths across which multiple devices and/or entitiesmay communicate. In some implementations, the network 115 may include apeer-to-peer network. The network 115 may also be coupled to or mayinclude portions of a telecommunications network for sending data in avariety of different communication protocols. In some implementations,the network 115 includes Bluetooth® communication networks or a cellularcommunications network for sending and receiving communications and/ordata including via short message service (SMS), multimedia messagingservice (MMS), hypertext transfer protocol (HTTP), direct dataconnection, wireless application protocol (WAP), e-mail, etc. Thenetwork 115 may also include a mobile data network that may includethird-generation (3G), fourth-generation (4G), long-term evolution(LTE), long-term evolution advanced (LTE-A), Voice-over-LTE (“VoLTE”) orany other mobile data network or combination of mobile data networks.Further, the network 115 may include one or more IEEE 802.11 wirelessnetworks.

The server 120 may store information for an item listing. Thisinformation may include, for example, text describing the item listedfor sale in the item listing, one or more images of the item listed forsale in the item listing, links or buttons that may be selected topurchase the item, etc. The server 120 may also include a database thatincludes information about all the items listed for sale or previouslylisted for sale in the marketplace. The database may include statisticaldata about the likelihood that one item, type of item, or category ofitem will likely have flaws and/or the type of flaws the item may likelyhave.

FIG. 2 illustrates a block diagram of a system 115 of some components ofthe server 120 according to some embodiments described herein. Theserver 120 may be arranged in accordance with at least one embodimentdescribed herein. The server 120 may include computing system 205 anddatabase 230. The computing system 205 may include a communicationinterface 210, a processor 215, a memory 220, and data storage 225. Oneor more of the communication interface 210, the processor 215, thememory 220, and the data storage 225 may be communicatively coupled.

In some embodiments, the communication interface 210 may be used by thecomputing system 205 to communicate with the network 115 and/or themobile device 105 of FIG. 1. In some embodiments, the communicationinterface 210 may communicate with the network 115 and/or the mobiledevice 105 using any communication protocol, interface, standard, etc.In some embodiments, the communication interface 210 may communicatewith the network 115 and/or the mobile device 105 using a wired orwireless connection.

In some embodiments, the processor 215 may include any suitablespecial-purpose or general-purpose computer, computing entity, orprocessing device including various computer hardware or softwaremodules and may be configured to execute instructions stored on anyapplicable computer-readable storage media. For example, the processor215 may include a microprocessor, a microcontroller, a digital signalprocessor (DSP), an application-specific integrated circuit (ASIC), aField-Programmable Gate Array (FPGA), or any other digital or analogcircuitry configured to interpret and/or to execute program instructionsand/or to process data. Although illustrated as a single processor inFIG. 2, it is understood that the processor 215 may include any numberof processors configured to perform individually or collectively anynumber of operations described herein. Additionally, one or more of theprocessors may be present on one or more different electronic devices,such as different servers. In some embodiments, the processor 215 mayinterpret and/or execute program instructions and/or process data storedin the memory 220, the data storage 225, or the memory 220 and the datastorage 225. In some embodiments, the processor 215 may fetch programinstructions from the data storage 225 and/or the database 230 and loadthe program instructions in the memory 220. After the programinstructions are loaded into the memory 220, the processor 215 mayexecute the program instructions.

In some embodiments, the memory 220 and the data storage 225 may includecomputer-readable storage media for carrying or havingcomputer-executable instructions or data structures stored thereon. Suchcomputer-readable storage media may be any available media that may beaccessed by a general-purpose or special-purpose computer, such as theprocessor 215. By way of example, and not limitation, suchcomputer-readable storage media may include tangible or non-transitorycomputer-readable storage media including Random Access Memory (RAM),Read-Only Memory (ROM), Electrically Erasable Programmable Read-OnlyMemory (EEPROM), Compact Disc Read-Only Memory (CD-ROM) or other opticaldisk storage, magnetic disk storage or other magnetic storage devices,flash memory devices (e.g., solid state memory devices), or any otherstorage medium which may be used to carry or store desired program codein the form of computer-executable instructions or data structures andwhich may be accessed by a general-purpose or special-purpose computer.Combinations of the above may also be included within the scope ofcomputer-readable storage media. Computer-executable instructions mayinclude, for example, instructions and data configured to cause theprocessor 215 to perform a certain operation or group of operations.

In some embodiments, the database 230 may be communicatively coupledwith the computing system 205. The database 230 may include one or moreother databases such as, for example, a serial number database 235, aprice database 240, a user profile database 250, a listing database 255,a template database 255, an image-flaw database 260, a filter database270, and a flaw profile database 265. The database 230 may also includemultiple modules, that when executed by the processor 215, may cause thecomputing system 205 to perform operations that may create a listing forthe mobile device 105 based on metadata received from the mobile device105.

In some embodiments, the database 230 may include computer-readablestorage media for carrying or having computer-executable instructions ordata structures stored thereon. Such computer-readable storage media maybe any available media that may be accessed by a general-purpose orspecial-purpose computer, such as the processor 215. By way of example,and not limitation, such computer-readable storage media may includetangible or non-transitory computer-readable storage media includingRandom Access Memory (RAM), Read-Only Memory (ROM), ElectricallyErasable Programmable Read-Only Memory (EEPROM), Compact Disc Read-OnlyMemory (CD-ROM) or other optical disk storage, magnetic disk storage orother magnetic storage devices, flash memory devices (e.g., solid statememory devices), or any other storage medium which may be used to carryor store desired program code in the form of computer-executableinstructions or data structures and which may be accessed by ageneral-purpose or special-purpose computer. Combinations of the abovemay also be included within the scope of computer-readable storagemedia. Computer-executable instructions may include, for example,instructions and data configured to cause the processor 215 to perform acertain operation or group of operations.

In some embodiments, the user profile database 250 may includeinformation related to various users of the electronic marketplace. Foreach user, this information may include, for example, demographic data,which may include, the age, gender, ethnicity, among other data, a userlocation, a shopping history, a purchasing history, items most recentlyviewed, items most recent items purchased, items most recent itemsplaced in a virtual shopping cart but not purchased, preferred shippingoptions, credit card information, listing information, an address, atelephone number, flaw history, etc.

In some embodiments, the user profile database 250 may also includelisting preferences for users. The listing preferences of a user mayinclude auction preferences, auction duration preferences, shippingpreferences, store front graphics, store name, user name, comments,ratings, payment preference, flaw display preferences, or somecombination thereof.

In some embodiments, the listing database 255 may include listings ofproducts listed for sale in the server 120. The listing database 255 mayalso include listings of products that have been created but notpublished. The listing database 255 may include the description of itemslisted for sale and/or items previously listed for sale. In someembodiments, the listing database 255 may reference images stored in theimage-flaw database 260.

In some embodiments, the image-flaw database 260 may include a pluralityof images that have been uploaded for display within an item listing.For example, each item listing may be associated with one or more imagesstored in the image-flaw database 260. In some embodiments, theimage-flaw database 260 may include different versions of an image.

In some embodiments, the image-flaw database 260 may include a listingof items or categories of items and the likelihood of the item beingflawed when listed. For example, the image-flaw database 260 may includean entry that specifies that a certain type of clothing has a highlikelihood of having a discoloration. As another example, the image-flawdatabase 260 may include an entry that specifies that a certain type ofelectronic device commonly has a scratch. As another example, theimage-flaw database 260 may include an entry that specifies that acertain type of handheld device commonly has a defective screen.

In some embodiments, the flaw profile database 265 may include aplurality of digital image filters that may be applied to an imageeither in real time or prior to being displayed to a user. These digitalimage filters may include, for example, contrast accentuation digitalimage filters, color inversion digital image filters, spatial domaindigital image filters, and detecting digital image filters, unsharpdigital image filters, Laplacian digital image filters, Gaussian digitalimage filters, smoothing digital image filters, etc.

In some embodiments, the filter database 270 may include data specifyingthe type of digital image filters that may be used for specific items orcategories of items to accent typical flaws in the items or thecategories of items. In some embodiments one or more digital imagefilters may be returned from the filter database 270 and applied to oneor more images based on the type of flaw. In some embodiments, one ormore digital image filters may be returned from the filter database 270and applied to one or more images based on the item type or itemcategory.

Modifications, additions, or omissions may be made to the server 120without departing from the scope of the present disclosure. For example,the computing system 205 and the database 230 may be communicativelycoupled by a network, such as the network 115 of FIG. 1. Alternately oradditionally, the server 120 may include multiple computing systems 205that may operate to execute one or more of the processes described inthis disclosure.

FIG. 3 is a flowchart of an example process 300 for listing an item inan online marketplace. One or more steps of the process 300 may beimplemented, in some embodiments, by one or more components of theserver 120 of FIG. 1 and FIG. 2. Although illustrated as discreteblocks, various blocks may be divided into additional blocks, combinedinto fewer blocks, performed in a different order, or eliminated,depending on the desired implementation.

Process 300 starts at block 305 where an image and/or product listinginformation are received at the server 120 from a seller, for example,from the seller through a user device (e.g., the mobile device 105 orthe computer 110). The listing information may include a description ofthe item to be listed for sale in the online marketplace and/or one ormore images of the item being listed. The listing information may alsoinclude an item type, an item category, etc.

At block 310 the item listing may be created. The item listing, forexample, may include a title, a description, the text received from theseller, and/or the images provided by the seller. The item listing mayalso include, for example, a sales price, an opening bid price, acurrent price, shipping prices, shipping methods, etc. The item listingmay include various other elements or characteristics. The item listing,for example, may be a webpage or series of webpages or other digitalmedia that may be presented to buyers through the online marketplace.The item listing may include an item type and or category that is eitherprovided by the seller or provided by the online marketplace based onthe text received from the seller.

At block 315 a flaw analysis may be performed on the images provided bythe seller. The flaw analysis, for example, may include performing anitem specific or a category specific flaw analysis based on the specificitem and or category of item. For example, a specific digital imagefilter may be applied to the images based on the type of item or thecategory of item. For example, using the item type or item category theserver 120 may identify a typical flaw using the flaw profile database265. Based on the typical flaw, a digital image filter may be selectedfrom the filter database 270 and applied to the one or more of theimages of the item.

As another example, the text provided by the seller may indicate thatthe item in the item listing includes a certain type of flaw. Based onthe certain type of flaw, a digital image filter may be selected fromthe filter database 270 and applied to the one or more images of theitem.

At block 320, the item listing may be presented in the onlinemarketplace. The item listing may include one or more of the originalimages, one or more digital image filtered images, or a combinationthereof. In some embodiments, the digital image filtered images may beavailable but not provided as part of the item listing. In someembodiments, the item listing may be provided to a plurality of usersthrough a webpage, an app, a mobile app, or an application. In someembodiments, the item listing may be provided in one or more markuplanguage such as, for example, HTML and/or XML.

At block 325, flaw accentuation tools may be provided to the sellerthrough a webpage, an app, and/or an application. For example, as partof the flaw accentuation tool provided to a seller, the seller may beable to click on a link or an image and a digitally filtered image or adigitally filtered portion of an image may be provided. As anotherexample, the user may be provided with tools that allow the user tohighlight, circle, zoom into, point to, or flag, etc. one or moreportions of an image.

As another example, the flaw accentuation tools may be provided as partof the item listing and may include an original image with a slider barthat allows a user to slide back and forth. For example, as the user(e.g., buyer or seller) slides the slider back-and-forth a digital imagefilter may be applied to the image and/or portions of the image. Asanother example, digitally filtered images may be displayed in place ofportions or the entire original image. In some embodiments, the slidermay increase one or more parameters of the digital filter. For example,if the digital filter is a contrast filter, the slider may be used toincrease or decrease the amount of contrast applied to the image. Asanother example, if the digital filter is an unsharp digital imagefilter, the slider may be used to increase or decrease the amount ofedge accentuation that occurs in the accentuated image by changingparameters (e.g., a scaling constant such as, for example, the k scalingconstant) in the filter.

In some embodiments, flaw accentuation tools may allow the user toselect various digital image filters that may be applied to portions orthe entire original image. For example, a drop down menu or other menumay be provided to the user that allows the user to select one or moredigital filters that may be applied to the image. In response, one ormore images may be presented through the item listing having the one ormore digital filters applied to an image provided by a seller.

In some embodiments, at block 325 the flaw accentuation tools may beprovided to the seller. For example, the seller may be able to modifythe item listing to include one or more flaw accentuations or flawaccentuation tools in the item listing.

In some embodiments, at block 325 the flaw accentuation tools may beprovided to a buyer. For example, the flaw accentuation tools providedto a buyer may allow the buyer to accent one or more images in the itemlisting. For example, the slider bar discussed above may be provided toallow the buyer to change, modify, and/or apply filters to one or moreimages.

FIG. 4 is a flowchart of an example process 400 providing flaw analysis,flaw presentation, and ranking based on the flaw analysis. One or moresteps of the process 400 may be implemented, in some embodiments, by oneor more components of server 120 of FIG. 1 and FIG. 2. Althoughillustrated as discrete blocks, various blocks may be divided intoadditional blocks, combined into fewer blocks, performed in a differentorder, or eliminated, depending on the desired implementation. In someembodiments, only one or a couple of blocks of process 400 may beperformed.

Process 400 starts at block 405 where an explicit flaw analysis isperformed. An explicit flaw analysis may include any type of flawidentification provided by a seller listing an item for sale in theonline marketplace. For example, as part of the listing creation processthe seller may be asked whether there is a flaw in the item being listedin the online marketplace. If the seller indicates that there is a flawon the item, then a user interface may be provided, such as, forexample, through a web browser that allows the seller to circle, pointto, or highlight the flaw in one or more images of the item being listedfor sale in the online marketplace. For example, a drawing tool may beprovided to allow the seller to circle the flaw with a line in the imageas shown in FIG. 5B. As another example, an ellipse drawing tool may beprovided to allow the seller to circle the flaw in the image as shown inFIG. 5C. As another example, an arrow tool may be provided to allow theseller to point to the flaw in the image as shown in FIG. 5D. As anotherexample, a text tool may be provided to allow the seller to add textregarding the flaw in the image as shown in FIG. 5D.

In some embodiments, the explicit flaw analysis 405 may provide a userinterface that queries the seller whether the item includes a flaw.

In some embodiments, the explicit flaw analysis 405 may provide a userinterface where the seller may upload an additional image. For example,the seller may upload an image that is taken of the specific flaw or iszoomed in to focus on the specific flaw.

In some embodiments, the explicit flaw analysis 405 may provide a userinterface that includes a zoom tool. The zoom tool, for example, may beused by the seller to zoom in on the area where the flaw is and/orprovide a separate image of the zoomed in area of the flaw.

In some embodiments, the explicit flaw analysis 405 may provide a userinterface that includes various digital image filter tools. For example,the user interface may allow the seller to apply one or more digitalimage filters, for example, selected from the filter database 270 thatmay highlight or emphasize the flaws in the image. For sample, an imageprovided by the seller during the online listing process may be providedto the seller in a user interface and one or more buttons or sliders mayalso be provided allowing the seller to turn on or off one or moredigital image filters and/or allowing the seller to increase or decreasethe intensity (or another factor) of one or more digital image filters.For example, these digital image filters may include a contrast digitalimage filter, a color saturation digital image filter, an unsharpdigital image filter, a Laplacian digital image filter, a Gaussiandigital image filter, a smoothing digital image filter, etc. Thesedigital image filters may include any digital image filter located inthe filter database 270.

At block 410 an implicit flaw analysis may be performed. In someembodiments, an implicit flaw analysis may be conducted by the server120 in response to information provided by the seller in text and/orimage format. In some embodiments, an implicit flaw analysis may beconducted by the server 120 without interaction with the seller. In someembodiments, the implicit flaw analysis 410 may flag the item as flawedbased on text entered by the seller, the type of item being listed, theitem category of the item, or an analysis performed on one or moreimages of the item provided by the seller.

In some embodiments, an implicit flaw analysis 410 may flag the item asflawed if the seller enters text into the description of the itemindicating that the item may have flaws. For example, an implicit flawanalysis may flag the item as flawed if any terms associated with a flawor derivatives thereof appear in the description of the item. Theseterms may include, for example, “damaged”, “ding”, “scratch”, “dent”,“discoloration”, “faded”, “soiled”, “used”, “old”, “stained”, “damage”,“hole”, “water damage”, “chip”, “defect”, etc.

In some embodiments, the totality of the description may be used tolimit whether to trigger an implicit flaw analysis. For example, if theitem is a golf club and the term “chip” w ‘0’ is used in thedescription, it is likely used to describe the type of golf club ratherthan any flaw in the golf club. As another example, if the item islisted as an antique, then it may be assumed to have flaws and,therefore, may not trigger the implicit flaw analysis despite usingterms associated with a flaw.

In some embodiments, an implicit flaw analysis 410 may flag the item asflawed based on the item type or the category of the item. For example,some items, item types, or categories of items may be more or lesslikely to have a flaw. The flaw profile database 265, for example, mayinclude a listing of items, item types, or categories of items that aretypically associated with a flaw. If the item, item type, or category ofitem matches the listing of items, item types, or categories of items inthe flaw profile database 265 associated with items likely to have aflaw, then the implicit flaw analysis may flag the item as flawed.

In some embodiments, an implicit flaw analysis 410 may flag the item asflawed if an analysis of an image indicates that the image may have beenaltered or may indicate that the item is flawed. For example, theimplicit flaw analysis 410 may use a digital image filter (e.g., fromthe filter database 270) and/or image forensic analysis to determinewhether the image has been altered with photo-editing software. Thedigital image filter and/or image forensic analysis, for example, mayuse an error level analysis (ELA) tool that can determine the amount ofdifference that occurs during a JPEG resave. Various other techniquesmay also be used. In some embodiments, the implicit flaw analysis 410may determine whether a digital image filter and/or image forensicanalysis has been applied to an image to decrease the likelihood that aflaw may be seen by a potential buyer.

As another example, the implicit flaw analysis 410 may review themetadata associated with the image to determine whether the image hasbeen altered by photo editing software. The metadata indicates that theimage was last saved by a photo editing application such as, forexample, Photoshop, Illustrator, Corel Draw, Pixlr, Serif PhotoPlus,Acorn, GIMP, Affinity Photo, Adobe Lightroom, ACDSee, Corel PaintShop,Aperture, DxO Optics, Pixelmator, etc. Some images, for example, mayinclude XMP metadata that may include a history field. If the historyfield indicates that the image was saved multiple times, then the imagewas likely modified. In some embodiments, the implicit flaw analysis maycheck whether the image includes an XMP metadata history field withentries above a threshold. If it does, then the image may be determinedto have been altered.

In some embodiments, the presence of XMP metadata itself may indicatethat the image was opened and/or saved by an Adobe® product and mayindicate that the image was edited by an Adobe® product such as, forexample, Photoshop. In some embodiments, the implicit flaw analysis maycheck whether the image includes XMP metadata. If it does, then theimage may be determined to have been altered.

In some embodiments, the implicit flaw analysis 410 may use an onlinethird-party forensic analysis service to determine whether an image wasaltered. For example, the image may be uploaded to a webpage thatperforms forensic analysis such as, for example, www.fotoforensics.com,www.imageforensic.org, www.izitru.com, imageedited.com, etc. Theimplicit flaw analysis 410 may determine whether the image has beenaltered based on the results provided by the third party webpage.

In some embodiments, an implicit flaw analysis 410 may flag the item asflawed if it is determined that the image includes effects known to beindicative of a digitally modified image such as, for example, if theimage includes rainbowing, etc. The image may be processed to determinewhether it was digitally modified using any number of techniques suchas, for example, error level analysis, principal component analysis, PCAcross-product, etc. Error level analysis, for example, comparesseparation between the red and blue color channels in the image.Principal component analysis (PCA), for example, identifies anorthogonal coordinate system based on the variance of the data space.The PCA cross-product can compare the various features of the imagebetween the PCA vector and another image vector such as a vector fromthe center of a color cloud to a specific color.

In some embodiments, if the implicit flaw analysis 410 may determinethat the image has been altered, the marketplace may provide a promptasking the seller to provide a new image of the item.

In some embodiments, the implicit flaw analysis 410 may compare theimage of the item being listed with one or more images of the same itemor item type and determine whether any variations between the two imagesindicate a flaw in the item being listed. The one or more images of thesame item or item type may be extracted, for example, from the listingdatabase 255. The comparison between the two images may provide anindication that the image being listed includes a flaw. Prior to makinga comparison, for example, the two images may be scaled so they are thesame size and/or background or foreground item may be removed. Thedifference in value of each pixel may be calculated. The areas wherethere is a concentration of different values above a predeterminedthreshold may indicate a flaw in the image of the item being listed.

FIGS. 5A, 5B, 5C, and 5D illustrate examples of a user interface forflaw marking and/or flaw presentation according to some embodiments. InFIG. 5A item 505 is presented to a user interface 500 and has flaw 550.In this example, item 505 is an Adirondack chair and the flaw is a gougein the arm rest in the chair. A number of tools are provided to theseller through the user interface: a drawing tool 510, a circle tool515, an arrow tool 520, a text tool 525, and a zoom tool 530. Variousother tools may be included. While a number of tools are shown in FIG.5A, some of these tools may or may not be included in the user interface500.

FIGS. 5B, 5C, and 5D each show an example where the seller has indicateda flaw in an image of the item being listed for sale. FIG. 5B shows acircle 555 drawn around the flaw 550 by the seller using the draw tool510. FIG. 5C shows a circle 560 drawn around the flaw 550 by the sellerusing the circle tool 515. FIG. 5D shows an arrow 565 pointing to theflaw 550 and text 570 identifying the flaw. The arrow 565 may have beendrawn with the arrow tool 520 and the text 570 may have been added usingthe text tool 525.

In some embodiments, the implicit flaw analysis 410 may determinewhether a digital display has a flaw using, for example, process 600shown in FIG. 6. One or more steps of the process 600 may beimplemented, in some embodiments, by one or more components of server120 of FIG. 1 and FIG. 2. Although illustrated as discrete blocks,various blocks may be divided into additional blocks, combined intofewer blocks, performed in a different order, or eliminated, dependingon the desired implementation. In some embodiments, only one or a coupleof blocks of process 600 may be performed.

Process 600 starts at block 605 where it may be determined whether theitem includes a digital display. For example, it can be determined ifthe item includes a digital display based on keywords found in the text,the item type, the item category, etc. For example, if the item is acomputer, a television, a mobile phone, a tablet, etc., then it can beassumed to include a digital display.

At block 610 process 600 may provide the seller with a sample image todisplay on the digital display of the item. For example, the seller maybe directed to a specific webpage or provided with a specific file ofthe sample image that may be displayed on the digital display of theitem.

At block 615 a digital photograph of the sample image may be receivedfrom the seller. For example, the seller may be directed to take adigital image of the digital display of the item while the digitaldisplay is displaying a sample image. A user interface may be providedto the seller that allows the seller to upload a digital photograph ofthe display displaying the sample image. In response, the seller mayupload a digital photograph.

At block 620, a comparison between the digital photograph and the sampleimage may be made. For example, a pixel by pixel or region by regioncomparison of the digital photograph with the sample image may be made.For example, the process 600 may take an average of regions of thedigital photograph and compare these values with an average of acorresponding region of the sample image. If the difference between aregion of the sample image and a region of the digital photograph isgreater than a threshold value, then the region of the displaycorresponding to the comparison may be flawed.

The threshold value, in some embodiments, may be determined based on anaverage difference between the pixels of the digital photograph and thesample image. For example, the threshold value may be greater than theaverage difference between the pixels of the digital photograph and thesample image.

In some embodiments, an identified flaw may be presented or highlightedto buyers (or sellers) at the online marketplace at block 415 in any ofa number of different ways. For example, one or more additional imagesmay be provided in the item listing of the online marketplace thatidentifies the flaw, highlights the flaw, helps the flaw stand out, etc.For example, these one or more images may include the image uploaded bythe seller and altered in such a way as to identify the flaw, highlightthe flaw, help the flaw stand out, etc. The images, for example, may bean image of a zoomed portion of the image that includes the flaw, theimage may have a digital image filter applied to the image from thefilter database 270 that may better show the flaw relative to otherportions of the image, the image may include one or more lines circlingthe flaw (see FIGS. 5B & 5C), the image may include one or more lines orarrows pointing to the flaw (see FIG. 5D), the image may include textdescribing the flaw, etc.

In some embodiments, a flaw highlight tool may be provided in a userinterface in conjunction with an image of the item. The flaw highlighttool may allow the seller to interact with the image to highlight flawswithin the image. For example, when the user passes the flaw tool over aportion of the image in the user interface, a digital image filter maybe applied to the image that highlights one or more flaws. Alternativelyor additionally, as the user passes the flaw tool over a portion of theimage in the user interface, at least a portion of a second image of theitem may be displayed in the user interface. The second image of theitem may be an image that has had a digital image filter applied to theimage that can highlight flaws in the image. The digital image filter,for example, may be a digital image filter selected from the filterdatabase 270. A buyer may be able to select the flaw tool and byinteracting with the image the buyer may be able to view highlightedflaws within the image.

As another example, the flaw highlight tool, for example, may includeone or more slider widgets in the user interface. The user may interactwith the one or more slider widgets to change the type, amount, and/orthe location of digital image filtering applied to the image. Thedigital image filter, for example, may be a digital image filterselected from the filter database 270. For example, as the user moves aslider widget in the user interface the image may be more or lessprocessed in real time. As another example, as the user moves a sliderwidget in the user interface the amount of processing of the image mayincrease or decrease in accordance with the position of the sliderwidget. As another example, as the user moves a slider widget in theuser interface the location of the processing in the image may change inaccordance with the position of the slider widget.

In some embodiments, a ranking of the item listing in the onlinemarketplace may be changed 420 based on the explicit flaw analysis 405and/or the implicit flaw analysis 410. Rankings indicate the order inwhich an item listing may be presented with respect to other itemlistings to buyers in response to a search query. Often, the morerelevant the item is to the search query, the higher the ranking and themore likely a potential buyer may view and purchase the item. Otherfactors that may affect rankings may include, for example, the relevanceof the item and the search terms, the amount of text provided by theseller, the price of the item, the number of images provided by theseller, the rating of the seller, or the rating of items having the sameor similar item types, etc.

In some embodiments, sellers may be encouraged and/or positivelyreinforced to positively indicate that an item includes flaws and/or toprovide some type of an indication of the flaw. For example, if a flawis indicated in the explicit flaw analysis 405, and the seller does notprovide any additional images of the item, or provide any flawaccentuations to an image, etc., then the listing may be provided with alower ranking than a seller that provides additional images of an itemand/or applies any flaw accentuations to the image of the item.Alternatively or additionally, an item listing may lose a predeterminednumber of ranking points in response to a seller that does not provideany additional images of the item, or provide any flaw accentuations toan image, etc.

In some embodiments, an item listing may gain a predetermined number ofranking points in response to a seller that does provide any additionalimages of the item and/or provides any flaw accentuations to an image,etc.

In some embodiments, an item listing may gain ranking points if it isdetermined that the item, item type, or item category is consistent withan item, an item type, and/or a category that typically is associatedwith a flaw, yet no flaw is identified by the seller in the implicitflaw analysis 410 and/or in the explicit flaw analysis 405.Alternatively, in some embodiments, an item listing may lose rankingpoints if it is determined that the item, item type, or item category isconsistent with an item, an item type, and/or a category that typicallyis associated with a flaw, yet no flaw is identified by the seller inthe implicit flaw analysis 410 and/or in the explicit flaw analysis 405.

In some embodiments, the magnitude of a ranking increase may beproportional to the number of flaw accentuations provided by the seller.For example, if the seller provides multiple flaw accentuations to oneor more images, the ranking of the item in a search query may beincreased by more ranking points in comparison to if the seller provideda single flaw accentuation or no flaw accentuation.

In some embodiments, the ranking of the item in a search query may beincreased if the seller provides one or more images of the flaw.

In some embodiments, if it is determined in the implicit flaw analysis410 that the image of an item has been altered, then the item rankingmay be decreased a predetermined number of points. Alternatively oradditionally, in some embodiments, if it is determined in the implicitflaw analysis 410 that the image of an item has been altered, then theitem may not be offered for sale in the online marketplace or removedfrom the online marketplace. Alternatively or additionally, in someembodiments, the rating of the seller may be reduced a predeterminednumber of points if it is determined that an image of an item has beenaltered. Alternatively or additionally, in some embodiments, the itemmay be listed for sale in the online marketplace with an indication suchas, for example, text and/or an image, indicating that one or more ofthe images has been altered by the seller.

Some embodiments include digital image filters that may be used todetermine whether an image includes a flaw. These digital image filtersor algorithms applying the digital image filter, for example, may bestored in the filter database 270. Any number or type of digital imagefilters may be applied to an image to determine whether the imageincludes a flaw or to process the image to highlight any potentialflaws.

In some embodiments, a training set of previously listed items with aflaw may be used to identify digital image filters that produce digitalimage filtered images that highlight specific types of flaws. A machinelearning algorithm such as, for example, a support vector machine, aneural net, or other supervised learning models, can be used toassociate digital image filters with specific flaws. In someembodiments, the machine learning algorithm can act on item listings(e.g., previously listed items) in the listing database 255. Forexample, the machine learning algorithm can be applied to a set of itemlistings that are known to include a flaw and/or have a flaw identifiedin one or more images. The set of item listings may also include anindication of the type of flaw on the item. The machine learningalgorithm can iteratively apply one or more digital image filters toeach image in the set of item listings and based on user feedback, imageanalysis, or image comparison, the best digital image filter can bedetermined. The machine learning algorithm may then associate the bestdigital image filter with the item type and/or associate the bestdigital image filter with the type of flaw. The machine learningalgorithm, for example, may provide a database that associates digitalimage filters with item type and/or flaw type, etc. The database, forexample, may grow or be revised as more item listings are analyzed overtime. The database may be stored, for example, in the filter database270.

Some embodiments may include a method for providing flaw accentuation toan image in an e-commerce online marketplace. The method may includereceiving at an online marketplace, from a seller through the Internet,an image of an item being listed for sale at the online marketplace;providing a first user interface to the seller through the Internet thatallows the seller to indicate whether the item has one or more flaws. Inresponse to the user indicating through the first user interface thatthe item has one or more flaws, providing the seller with one or moredigital flaw accentuation tools through the first user interface;receiving through the first user interface a flaw accentuation to theimage that is based on an interaction between the seller and a flawaccentuation tool; and creating a listing in the online marketplace forthe item that includes the image and an application of the flawaccentuation to the image.

In some embodiments, the flaw accentuation to the image comprises anindication from the user to apply a digital image filter to the imagecreating a second image; and/or the application of the flaw accentuationcomprises displaying the image and providing a tool to the buyer thatallows the buyer to manipulate a user interface item that alternativelydisplays portions of the second image in place of the first image.

In some embodiments, the accentuation tool may include at least one toolselected from the group consisting of: a lasso tool, a line drawingtool, an ellipse drawing tool, a text tool, an arrow tool, a zoom tool,and a digital image filter application tool.

In some embodiments, the flaw accentuation to the image may include anaccentuation selected from the group consisting of: providing a linearound a flaw, insertion of text into the image, insertion of an arrowinto the image, zooming into a portion of the image, and applying adigital image filter to the image.

In some embodiments, applying a digital image filter to the image mayinclude applying a digital image filter selected from the listconsisting of a contrast accentuation digital image filter, colorinversion digital image filter, spatial domain digital image filter, anddetecting digital image filters, unsharp digital image filter, Laplaciandigital image filter, Gaussian digital image filter, and smoothingdigital image filter.

In some embodiments, the flaw accentuation to the image is provided in asecond image comprising the image and the flaw accentuation.

The term “substantially” means within 5% or 10% of the value referred toor within manufacturing tolerances.

Numerous specific details are set forth herein to provide a thoroughunderstanding of the claimed subject matter. However, those skilled inthe art will understand that the claimed subject matter may be practicedwithout these specific details. In other instances, methods,apparatuses, or systems that would be known by one of ordinary skillhave not been described in detail so as not to obscure claimed subjectmatter.

Some portions are presented in terms of algorithms or symbolicrepresentations of operations on data bits or binary digital signalsstored within a computing system memory, such as a computer memory.These algorithmic descriptions or representations are examples oftechniques used by those of ordinary skill in the data processing art toconvey the substance of their work to others skilled in the art. Analgorithm is a self-consistent sequence of operations or similarprocessing leading to a desired result. In this context, operations orprocessing involves physical manipulation of physical quantities.Typically, although not necessarily, such quantities may take the formof electrical or magnetic signals capable of being stored, transferred,combined, compared, or otherwise manipulated. It has proven convenientat times, principally for reasons of common usage, to refer to suchsignals as bits, data, values, elements, symbols, characters, terms,numbers, numerals, or the like. It should be understood, however, thatall of these and similar terms are to be associated with appropriatephysical quantities and are merely convenient labels. Unlessspecifically stated otherwise, it is appreciated that throughout thisspecification discussions utilizing terms such as “processing,”“computing,” “calculating,” “determining,” and “identifying” or the likerefer to actions or processes of a computing device, such as one or morecomputers or a similar electronic computing device or devices, thatmanipulate or transform data represented as physical, electronic, ormagnetic quantities within memories, registers, or other informationstorage devices, transmission devices, or display devices of thecomputing platform.

The system or systems discussed herein are not limited to any particularhardware architecture or configuration. A computing device can includeany suitable arrangement of components that provides a resultconditioned on one or more inputs. Suitable computing devices includemultipurpose microprocessor-based computer systems accessing storedsoftware that programs or configures the computing system from ageneral-purpose computing apparatus to a specialized computing apparatusimplementing one or more embodiments of the present subject matter. Anysuitable programming, scripting, or other type of language orcombinations of languages may be used to implement the teachingscontained herein in software to be used in programming or configuring acomputing device.

Embodiments of the methods disclosed herein may be performed in theoperation of such computing devices. The order of the blocks presentedin the examples above can be varied—for example, blocks can bere-ordered, combined, and/or broken into sub-blocks. Certain blocks orprocesses can be performed in parallel.

The use of “adapted to” or “configured to” herein is meant as open andinclusive language that does not foreclose devices adapted to orconfigured to perform additional tasks or steps. Additionally, the useof “based on” is meant to be open and inclusive, in that a process,step, calculation, or other action “based on” one or more recitedconditions or values may, in practice, be based on additional conditionsor values beyond those recited. Headings, lists, and numbering includedherein are for ease of explanation only and are not meant to belimiting.

While the present subject matter has been described in detail withrespect to specific embodiments thereof, it will be appreciated thatthose skilled in the art, upon attaining an understanding of theforegoing, may readily produce alterations to, variations of, andequivalents to such embodiments. Accordingly, it should be understoodthat the present disclosure has been presented for-purposes of examplerather than limitation, and does not preclude inclusion of suchmodifications, variations, and/or additions to the present subjectmatter as would be readily apparent to one of ordinary skill in the art.

What is claimed is:
 1. A method for providing flaw accentuation to adigital image, the method comprising: receiving, at one or more servers,an image of an item; applying, by the one or more servers, one or moredigital image filters to at least a portion of the image to highlightdeviations in condition of the item; based on the image having appliedthereto the one or more digital image filters, determining, by the oneor more servers, that the item includes a flaw, wherein the flawincludes damage to the item; in response to a determination that theitem includes the flaw, creating, by the one or more servers, a flawaccentuation to the image that modifies the image such that the flawstands out; and further creating, by the one or more servers, a listingin the e-commerce online marketplace for the item, the listing includingthe image and the flaw accentuation to the image.
 2. The method of claim1, further comprising demoting a ranking of the created listing tochange an order of items displayed to a buyer in response to a receivedsearch request.
 3. The method of claim 2, further comprising causingdisplay of the created listing for the item consistent with a changedorder of items responsive to the received search request.
 4. The methodof claim 1, further comprising receiving text that describes the itemfrom a seller, wherein the determination of whether the item includesthe flaw is further based at least partially on the text.
 5. The methodof claim 4, wherein: the text indicates an item type; the determiningthat the item includes the flaw further includes looking up in adatabase one or more specific flaw types that are correlated with theitem type in the database; and the flaw accentuation is created based onthe one or more specific flaw types.
 6. The method of claim 4, whereinthe determining that the item includes the flaw includes determiningwhether the text includes a term selected from the list consisting ofscratch, chip, dent, fold, crack, water damage, stain, discoloration,fading, hole, ink stain, and gouge.
 7. The method of claim 1, furthercomprising determining whether the image is an altered image based onone or more or a combination of: metadata associated with the image;application of the one or more digital image filters to the image; and aforensic analysis of the image.
 8. The method of claim 7, furthercomprising sending a request to a seller through a network interface foran unaltered image in response to a determination that the image is analtered image.
 9. The method of claim 1, wherein the one or more digitalimage filters are selected from the list consisting of: a contrastaccentuation digital image filter, a color inversion digital imagefilter, a spatial domain digital image filter, detecting digital imagefilters, an unsharp digital image filter, a Laplacian digital imagefilter, a Gaussian digital image filter, and a smoothing digital imagefilter.
 10. The method of claim 1, further comprising: receiving userinput via a flaw accentuation tool; and based on the user input, varyingapplication of a characteristic of the one or more digital image filtersto the image.
 11. The method of claim 1, wherein the digital imagefilters are applied to the image either in real time or prior to beingdisplayed to a user.
 12. One or more non-transitory computer-readablemedia storing one or more programs that in response to execution by theone or more servers cause or direct a system to perform operations ofthe method of claim
 1. 13. A system, comprising: one or more processors;a network interface; and one or more non-transitory computer-readablemedia storing one or more programs that in response to execution by theone or more processors cause or direct the system to perform operationscomprising: applying a digital image filter to at least a portion of animage of an item, application of the digital image filter beingconfigured to highlight deviations in condition of the item; determiningthat the item includes a flaw that includes damage to the item based onthe image having applied thereto the digital image filter; responsive toa determination that the item includes the flaw, creating a flawaccentuation to the image that modifies the image such that the flawstands out; and further creating a listing in the online marketplace forthe item, the listing including the image and the flaw accentuation tothe image.
 14. The system of claim 13, wherein the operations furthercomprise: receiving a search request; demoting a ranking of the createdlisting to change an order of items displayed to a buyer in response toreceived search request; and causing display of the created listing forthe item consistent with a changed order of items.
 15. The system ofclaim 13, wherein: the operations further comprise receiving text thatdescribes the item from a seller; and the determination of whether theitem includes the flaw is further based at least partially on the text.16. The system of claim 15, wherein: the text indicates an item type;the determining that the item includes the flaw further includes lookingup in a database one or more specific flaw types that are correlatedwith the item type in the database; and the flaw accentuation is createdbased on the one or more specific flaw types.
 17. The system of claim15, wherein the determining that the item includes the flaw includesdetermining whether the text includes a term selected from the listconsisting of scratch, chip, dent, fold, crack, water damage, stain,discoloration, fading, hole, ink stain, and gouge.
 18. The system ofclaim 13, wherein the operations further comprise: determining whetherthe image is an altered image based on one or more or a combination of:metadata associated with the image; application of the digital imagefilter to the image; and a forensic analysis of the image; and sending arequest to a seller through a network interface for an unaltered imagein response to a determination that the image is an altered image. 19.The system of claim 13, wherein: the digital image filter is selectedfrom the list consisting of: a contrast accentuation digital imagefilter, a color inversion digital image filter, a spatial domain digitalimage filter, a detecting digital image filter, an unsharp digital imagefilter, a Laplacian digital image filter, a Gaussian digital imagefilter, and a smoothing digital image filter; and the digital imagefilter is applied to the image either in real time or prior to beingdisplayed to a user.
 20. The system of claim 13, wherein the operationsfurther comprise: receiving user input via a flaw accentuation tool; andbased on the user input, varying application of a characteristic of thedigital image filter to the image.